Matrix theory and linear algebra, including linear transformations and their matrices, systems of linear equations, determinants, eigenvalues, vector spaces, orthogonal matrices and bases, and reduced and canonical forms. Applications may include image compression, dynamical systems, stochastic matrices and Markov chains.
